Omics meets hypothesis-driven research

Curzio Rüegg; Jean-Daniel Tissot; Pierre Farmer; Agnese Mariotti

doi:10.1160/TH08-06-0348

Thrombosis and Haemostasis, Table of Contents

Thromb Haemost 2008; 100(05): 738-746
DOI: 10.1160/TH08-06-0348

Editorial Focus

Schattauer GmbH

Omics meets hypothesis-driven research

Partnership for innovative discoveries in vascular biology and angiogenesis

Curzio Rüegg

¹Division of Experimental Oncology, Centre Pluridisciplinaire d’Oncologie, Faculty of Biology and Medicine, University of Lausanne, Epalinges, Switzerland

²National Centre for Competence in Research (NCCR) Molecular Oncology, Epalinges, Switzerland

,

Jean-Daniel Tissot

³Service RégionalVaudois de Transfusion Sanguine, Lausanne, Switzerland

,

Pierre Farmer

²National Centre for Competence in Research (NCCR) Molecular Oncology, Epalinges, Switzerland

⁴Swiss Institute of Bioinformatics, Bioinformatics Core Facility, Quartier Sorge, Bâtiment Génopode, Lausanne, Switzerland

,

Agnese Mariotti

¹Division of Experimental Oncology, Centre Pluridisciplinaire d’Oncologie, Faculty of Biology and Medicine, University of Lausanne, Epalinges, Switzerland

› Author Affiliations

Abstract

Summary

The emergence of omics technologies allowing the global analysis of a given biological or molecular system, rather than the study of its individual components,has revolutionized biomedical research, including cardiovascular medicine research in the past decade. These developments raised the prospect that classical,hypothesis-driven,single gene-based approaches may soon become obsolete. The experience accumulated so far, however, indicates that omic technologies only represent tools similar to those classically used by scientists in the past and nowadays, to make hypothesis and build models, with the main difference that they generate large amounts of unbiased information.Thus,omics and classical hypothesis-driven research are rather complementary approaches with the potential to effectively synergize to boost research in many fields, including cardiovascular medicine. In this article we discuss some general aspects of omics approaches, and review contributions in three areas of vascular biology, thrombosis and haemostasis, atherosclerosis and angiogenesis, in which omics approaches have already been applied (vasculomics).

Keywords

Atherosclerosis - endothelial cells - gene expression - proteomics - cancer

Full Text

References

References
1 Weinstein JN. 'Omic' and hypothesis-driven research in the molecular pharmacology of cancer. Curr Opin Pharmacol 2002; 02: 361-365.
2 Evans GA. Designer science and the ”omic“ revolution. Nat Biotechnol 2000; 18: 127.
3 Ideker T, Galitski T, Hood L. A new approach to decoding life: systems biology. Annu Rev Genomics Hum Genet 2001; 02: 343-372.
4 Yu U, Lee SH, Kim YJ. et al. Bioinformatics in the post-genome era. J Biochem Mol Biol 2004; 37: 75-82.
5 Sotiriou C, Piccart MJ. Taking gene-expression profiling to the clinic: when will molecular signatures become relevant to patient care?. Nat Rev Cancer 2007; 07: 545-553.
6 Farmer P, Bonnefoi H, Becette V. et al. Identification of molecular apocrine breast tumours by microarray analysis. Oncogene 2005; 24: 4660-4671.
7 Subramanian A, Tamayo P, Mootha VK. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005; 102: 15545-15550.
8 Mootha VK, Lindgren CM, Eriksson KF. et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 2003; 34: 267-273.
9 Nelson PS, Clegg N, Arnold H. et al. The program of androgen-responsive genes in neoplastic prostate epithelium. Proc Natl Acad Sci USA 2002; 99: 11890-11895.
10 Doane AS, Danso M, Lal P. et al. An estrogen receptor-negative breast cancer subset characterized by a hormonally regulated transcriptional program and response to androgen. Oncogene 2006; 25: 3994-4008.
11 Gospodarowicz M, Benedet L, Hutter RV. et al. History and international developments in cancer staging. Cancer Prev Control 1998; 02: 262-268.
12 Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000; 100: 57-70.
13 Vogelstein B, Kinzler KW. The multistep nature of cancer. Trends Genet 1993; 09: 138-141.
14 Liu ET. Classification of cancers by expression profiling. Curr Opin Genet Dev 2003; 13: 97-103.
15 Nuyten DS, van de Vijver MJ. Using microarray analysis as a prognostic and predictive tool in oncology: focus on breast cancer and normal tissue toxicity. Semin Radiat Oncol 2008; 18: 105-114.
16 Alaiya AA, Franzen B, Auer G. et al. Cancer proteomics: from identification of novel markers to creation of artifical learning models for tumor classification. Electrophoresis 2000; 21: 1210-1217.
17 Ludwig JA, Weinstein JN. Biomarkers in cancer staging, prognosis and treatment selection. Nat Rev Cancer 2005; 05: 845-856.
18 Troy GC. An overview of hemostasis. Vet Clin North Am Small Anim Pract 1988; 18: 5-20.
19 Ferrer-Antunes C. Polymorphisms of coagulation factor genes--a review. Clin Chem Lab Med 1998; 36: 897-906.
20 Anderson L, Anderson NG. High resolution two-dimensional electrophoresis of human plasma proteins. Proc Natl Acad Sci USA 1977; 74: 5421-5425.
21 Omenn GS. The Human Proteome Organization Plasma Proteome Project pilot phase: reference specimens, technology platform comparisons, and standardized data submissions and analyses. Proteomics 2004; 04: 1235-1240.
22 Berhane BT, Zong C, Liem DA. et al. Cardiovascular-related proteins identified in human plasma by the HUPO Plasma Proteome Project pilot phase. Proteomics 2005; 05: 3520-3530.
23 Scully MF. Plasma peptidome: A new approach for assessing thrombotic risk?. Thromb Haemost 2006; 96: 697.
24 Dittrich M, Birschmann I, Stuhlfelder C. et al. Understanding platelets. Lessons from proteomics, genomics and promises from network analysis. Thromb Haemost 2005; 94: 916-925.
25 Dittrich M, Birschmann I, Pfrang J. et al. Analysis of SAGE data in human platelets: features of the transcriptome in an anucleate cell. Thromb Haemost 2006; 95: 643-651.
26 Barelli S, Crettaz D, Thadikkaran L. et al. Plasma/ serum proteomics: pre-analytical issues. Expert Rev Proteomics 2007; 04: 363-370.
27 Ayache S, Panelli M, Marincola FM. et al. Effects of storage time and exogenous protease inhibitors on plasma protein levels. Am J Clin Pathol 2006; 126: 174-184.
28 Tammen H, Mohring T, Kellmann M. et al. Mass spectrometric phenotyping of Val 34Leu polymorphism of blood coagulation factor XIII by differential peptide display. Clin Chem 2004; 50: 545-551.
29 Mann KG, Brummel-Ziedins K, Undas A. et al. Does the genotype predict the phenotype? Evaluations of the hemostatic proteome. J Thromb Haemost 2004; 02: 1727-1734.
30 Pula G, Perera S, Prokopi M. et al. Proteomic analysis of secretory proteoins and vesicles in vascular research. Proteomics Clin Appl 2008 2008; 02: 882-889.
31 Piccin A, Murphy WG, Smith OP. Circulating microparticles: pathophysiology and clinical implications. Blood Rev 2007; 21: 157-171.
32 Smalley DM, Root KE, Cho H. et al. Proteomic discovery of 21 proteins expressed in human plasma-derived but not platelet-derived microparticles. Thromb Haemost 2007; 97: 67-80.
33 Tuomisto TT, Binder BR, Yla-Herttuala S. Genetics, genomics and proteomics in atherosclerosis research. Ann Med 2005; 37: 323-332.
34 Monajemi H, Arkenbout EK, Pannekoek H. Gene expression in atherogenesis. Thromb Haemost 2001; 86: 404-412.
35 Martinez-Gonzalez J, Rius J, Castello A. et al. Neuron-derived orphan receptor-1 (NOR-1)modulates vascular smooth muscle cell proliferation. Circ Res 2003; 92: 96-103.
36 Arkenbout EK, van Bragt M, Eldering E. et al. TR3 orphan receptor is expressed in vascular endothelial cells and mediates cell cycle arrest. Arterioscler Thromb Vasc Biol 2003; 23: 1535-1540.
37 van Thienen JV, Fledderus JO, Dekker RJ. et al. Shear stress sustains atheroprotective endothelial KLF2 expression more potently than statins through mRNA stabilization. Cardiovasc Res 2006; 72: 231-240.
38 Yan FF, Liu YF, Liu Y. et al. KLF4: a novel target for the treatment of atherosclerosis. Med Hypotheses 2008; 70: 845-847.
39 Lutgens E, Faber B, Schapira K. et al. Gene profiling in atherosclerosis reveals a key role for small inducible cytokines: validation using a novel monocyte chemoattractant protein monoclonal antibody. Circulation 2005; 111: 3443-3452.
40 Mayr M, Zampetaki A, Sidibe A. et al. Proteomic and metabolomic analysis of smooth muscle cells derived from the arterial media and adventitial progenitors of apolipoprotein E-deficient mice. Circ Res 2008; 102: 1046-1056.
41 Wu J, Liu W, Sousa E. et al. Proteomic identification of endothelial proteins isolated in situ from atherosclerotic aorta via systemic perfusion. J Proteome Res 2007; 06: 4728-4736.
42 Skogsberg J, Lundstrom J, Kovacs A. et al. Transcriptional profiling uncovers a network of cholesterol-responsive atherosclerosis target genes. PLoS Genet 2008; 04: e1000036.
43 Blanco-Colio LM, Martin-Ventura JL, Vivanco F. et al. Biology of atherosclerotic plaques: what we are learning from proteomic analysis. Cardiovasc Res 2006; 72: 18-29.
44 Sung HJ, Ryang YS, Jang SW. et al. Proteomic analysis of differential protein expression in atherosclerosis. Biomarkers 2006; 11: 279-290.
45 Almofti MR, Huang Z, Yang P. et al. Proteomic analysis of rat aorta during atherosclerosis induced by high cholesterol diet and injection of vitamin D3. Clin Exp Pharmacol Physiol 2006; 33: 305-309.
46 Bagnato C, Thumar J, Mayya V. et al. Proteomics analysis of human coronary atherosclerotic plaque: a feasibility study of direct tissue proteomics by liquid chromatography and tandem mass spectrometry. Mol Cell Proteomics 2007; 06: 1088-1102.
47 Wilson AM, Kimura E, Harada RK. et al. Beta2-microglobulin as a biomarker in peripheral arterial disease: proteomic profiling and clinical studies. Circulation 2007; 116: 1396-1403.
48 Duran MC, Martin-Ventura JL, Mas S. et al. Characterization of the human atheroma plaque secretome by proteomic analysis. Methods Mol Biol 2007; 357: 141-150.
49 Karlsson H, Leanderson P, Tagesson C. et al. Lipo-proteomics II: mapping of proteins in high-density lipoprotein using two-dimensional gel electrophoresis and mass spectrometry. Proteomics 2005; 05: 1431-1445.
50 Karlsson H, Leanderson P, Tagesson C. et al. Lipoproteomics I: mapping of proteins in low-density lipoprotein using two-dimensional gel electrophoresis and mass spectrometry. Proteomics 2005; 05: 551-565.
51 Yang PY, Rui YC, Yang PY. et al. Proteomic analysis of foam cells. Methods Mol Biol 2007; 357: 297-305.
52 Fach EM, Garulacan LA, Gao J. et al. In vitro biomarker discovery for atherosclerosis by proteomics. Mol Cell Proteomics 2004; 03: 1200-1210.
53 Mayr M, Madhu B, Xu Q. Proteomics and metabolomics combined in cardiovascular research. Trends Cardiovasc Med 2007; 17: 43-48.
54 Miller DT, Ridker PM, Libby P. et al. Atherosclerosis: the path from genomics to therapeutics. J Am Coll Cardiol 2007; 49: 1589-1599.
55 Carmeliet P. Angiogenesis in health and disease. Nat Med 2003; 09: 653-660.
56 Mittal V, Nolan DJ. Genomics and proteomics approaches in understanding tumor angiogenesis. Expert Rev Mol Diagn 2007; 07: 133-147.
57 Korherr C, Gille H, Schafer R. et al. Identification of proangiogenic genes and pathways by high-throughput functional genomics: TBK1 and the IRF3 pathway. Proc Natl Acad Sci USA 2006; 103: 4240-4245.
58 Jih YJ, Lien WH, Tsai WC. et al. Distinct regulation of genes by bFGF and VEGF-A in endothelial cells. Angiogenesis 2001; 04: 313-321.
59 Abe M, Sato Y. cDNA microarray analysis of the gene expression profile of VEGF-activated human umbilical vein endothelial cells. Angiogenesis 2001; 04: 289-298.
60 Schoenfeld J, Lessan K, Johnson NA. et al. Bioinformatic analysis of primary endothelial cell gene array data illustrated by the analysis of transcriptome changes in endothelial cells exposed to VEGF-A and PlGF. Angiogenesis 2004; 07: 143-156.
61 St Croix B, Rago C, Velculescu V. et al. Genes expressed in human tumor endothelium. Science 2000; 289: 1197-1202.
62 Seaman S, Stevens J, Yang MY. et al. Genes that distinguish physiological and pathological angiogenesis. Cancer Cell 2007; 11: 539-554.
63 Ghilardi C, Chiorino G, Dossi R. et al. Identification of novel vascular markers through gene expression profiling of tumor-derived endothelium. BMC Genomics 2008; 09: 201.
64 Bhati R, Patterson C, Livasy CA. et al. Molecular characterization of human breast tumor vascular cells. Am J Pathol 2008; 172: 1381-1390.
65 Abdollahi A, Hahnfeldt P, Maercker C. et al. Endostatin's antiangiogenic signaling network. Mol Cell 2004; 13: 649-663.
66 Favre CJ, Mancuso M, Maas K. et al. Expression of genes involved in vascular development and angiogenesis in endothelial cells of adult lung. Am J Physiol Heart Circ Physiol 2003; 285: H1917-1938.
67 Hardwick JS, Yang Y, Zhang C. et al. Identification of biomarkers for tumor endothelial cell proliferation through gene expression profiling. Mol Cancer Ther 2005; 04: 413-425.
68 Sessa C, Guibal A, Del Conte G. et al. Biomarkers of angiogenesis for the development of antiangiogenic therapies in oncology : tools or decorations?. Nat Clin Pract Oncol. 2008 05. in press.
69 Bruneel A, Labas V, Mailloux A. et al. Proteomic study of human umbilical vein endothelial cells in culture. Proteomics 2003; 03: 714-723.
70 Li A, Li H, Jin G. et al. A proteomic study on cell cycle progression of endothelium exposed to tumor conditioned medium and the possible role of cyclin D1/E. Clin Hemorheol Microcirc 2003; 29: 383-390.
71 Bruneel A, Labas V, Mailloux A. et al. Proteomics of human umbilical vein endothelial cells applied to etoposide-induced apoptosis. Proteomics 2005; 05: 3876-3884.
72 Godl K, Gruss OJ, Eickhoff J. et al. Proteomic characterization of the angiogenesis inhibitor SU6668 reveals multiple impacts on cellular kinase signaling. Cancer Res 2005; 65: 6919-6926.
73 Thompson LJ, Wang F, Proia AD. et al. Proteome analysis of the rat cornea during angiogenesis. Proteomics 2003; 03: 2258-2266.
74 Roesli C, Mumprecht V, Neri D. et al. Identification of the surface-accessible, lineage-specific vascular proteome by two-dimensional peptide mapping. Faseb J. 2008 in press.
75 Castronovo V, Waltregny D, Kischel P. et al. A chemical proteomics approach for the identification of accessible antigens expressed in human kidney cancer. Mol Cell Proteomics 2006; 05: 2083-2091.
76 Park HJ, Kim BG, Lee SJ. et al. Proteomic profiling of endothelial cells in human lung cancer. J Proteome Res 2008; 07: 1138-1150.
77 Dean RA, Butler GS, Hamma-Kourbali Y. et al. Identification of candidate angiogenic inhibitors processed by matrix metalloproteinase 2 (MMP-2) in cell-based proteomic screens: disruption of vascular endothelial growth factor (VEGF)/heparin affin regulatory peptide (pleiotrophin) and VEGF/Connective tissue growth factor angiogenic inhibitory complexes by MMP-2 proteolysis. Mol Cell Biol 2007; 27: 8454-8465.
78 Simonson AB, Schnitzer JE. Vascular proteomic mapping in vivo. J Thromb Haemost 2007; 05 (Suppl. 01) 183-187.
79 Acevedo L, Yu J, Erdjument-Bromage H. et al. A new role for Nogo as a regulator of vascular remodeling. Nat Med 2004; 10: 382-388.
80 Delbosc S, Haloui M, Louedec L. et al. Proteomic analysis permits the identification of new biomarkers of arterial wall remodeling in hypertension. Mol Med 2008; 14: 383-394.
81 Ribatti D, Vacca A, Roncali L. et al. The chick embryo chorioallantoic membrane as a model for in vivo research on angiogenesis. Int J Dev Biol 1996; 40: 1189-1197.
82 Hagedorn M, Javerzat S, Gilges D. et al. Accessing key steps of human tumor progression in vivo by using an avian embryo model. Proc Natl Acad Sci USA 2005; 102: 1643-1648.
83 Jin SW, Herzog W, Santoro MM. et al. A transgene-assisted genetic screen identifies essential regulators of vascular development in vertebrate embryos. Dev Biol 2007; 307: 29-42.
84 Lee P, Goishi K, Davidson AJ. et al. Neuropilin-1 is required for vascular development and is a mediator of VEGF-dependent angiogenesis in zebrafish. Proc Natl Acad Sci USA 2002; 99: 10470-10475.
85 Kidd KR, Weinstein BM. Fishing for novel angiogenic therapies. Br J Pharmacol 2003; 140: 585-594.
86 Rubinstein AL. Zebrafish: from disease modeling to drug discovery. Curr Opin Drug Discov Devel 2003; 06: 218-223.
87 Ny A, Autiero M, Carmeliet P. Zebrafish and Xenopus tadpoles: small animal models to study angiogenesis and lymphangiogenesis. Exp Cell Res 2006; 312: 684-693.
88 De Smet F, Carmeliet P, Autiero M. Fishing and frogging for anti-angiogenic drugs. Nat Chem Biol 2006; 02: 228-229.
89 Lawson ND, Weinstein BM. In vivo imaging of embryonic vascular development using transgenic zebrafish. Dev Biol 2002; 248: 307-318.
90 Link V, Shevchenko A, Heisenberg CP. Proteomics of early zebrafish embryos. BMC Dev Biol 2006; 06: 1.
91 Lemeer S, Pinkse MW, Mohammed S. et al. Online automated in vivo zebrafish phosphoproteomics: from large-scale analysis down to a single embryo. J Proteome Res 2008; 07: 1555-1564.
92 Bosworth CAt, Chou CW, Cole RB. et al. Protein expression patterns in zebrafish skeletal muscle: initial characterization and the effects of hypoxic exposure. Proteomics 2005; 05: 1362-1371.
93 Nicoli S, Ribatti D, Cotelli F. et al. Mammalian tumor xenografts induce neovascularization in zebrafish embryos. Cancer Res 2007; 67: 2927-2931.
94 Stoletov K, Klemke R. Catch of the day: zebrafish as a human cancer model. Oncogene 2008; 27: 4509-4520.
95 Nagamine K, Matsuda A, Asashima M. et al. XRASGRP2 expression during early development of Xenopus embryos. Biochem Biophys Res Commun 2008; 372: 886-891.
96 Sato K, Iwasaki T, Sakakibara K. et al. Towards the molecular dissection of fertilization signaling: Our functional genomic/proteomic strategies. Proteomics 2002; 02: 1079-1089.